Three-dimensional models of structures, such as famous landmarks, may be of interest to people all over the world, for use in navigation, education, and research. Current systems may create a three-dimensional point cloud model of a given entity via “structure-from-motion (SFM)” or “bundle adjustment” using multiple photos of the entity.
Current systems may require that a normal be associated with each of the points to fit a mesh to a point cloud. Often, these normals are recovered by fitting a plane to a point and its nearest neighbors. Yet, a given entity such as the Arc de Triomphe in Paris may have a complex geometry, and the nearest neighbors of a point may not belong to the same surface, which results in incorrect normals being fitted and leads to large errors in mesh creation. There is also a directional ambiguity in the fitted normal, because two solutions that point in opposite directions may both satisfy the same set of points. Accordingly, a need exists for systems, methods, and apparatus to address the shortfalls of present technology and to provide other new and innovative features.